Inference is the process of running a trained model to produce an output — for example generating a response or a prediction from an input. It's distinct from training, and its cost and latency are key production concerns.
Optimising inference (batching, caching, quantisation, the right hardware) is central to making AI features fast and affordable at scale.
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